Azure Virtual Machines (VMs) come in various sizes to cater to different workloads and requirements. Here's an overview of the main VM size categories and their characteristics:
General Purpose VMs
A-series: Entry-level, cost-effective VMs for dev/test, small databases, and low-traffic web servers.
Sizes: A0-A8 (1-8 vCPUs, 0.75-16 GB RAM)
B-series: Economical VMs for workloads with variable CPU usage, such as web servers, small databases, and dev/test environments.
Sizes: B1S-B20 (1-20 vCPUs, 0.5-80 GB RAM)
D-series: Balanced VMs for general-purpose workloads, such as medium-traffic web servers, networks, and enterprise applications.
Sizes: D2-D96 (2-96 vCPUs, 8-384 GB RAM)
Compute-Optimized VMs
F-series: High-performance VMs for compute-intensive workloads, such as gaming, scientific modeling, and data analytics.
Sizes: F2-F72 (2-72 vCPUs, 4-144 GB RAM)
H-series: High-performance VMs for HPC workloads, such as weather forecasting, fluid dynamics, and molecular modeling.
Sizes: H8-H16r (8-16 vCPUs, 56-112 GB RAM)
Memory-Optimized VMs
E-series: High-memory VMs for memory-intensive workloads, such as large databases, data warehousing, and data analytics.
Sizes: E2-E64 (2-64 vCPUs, 16-432 GB RAM)
G-series: High-memory VMs for large-scale databases, data warehousing, and big data analytics.
Sizes: G1-G5 (2-32 vCPUs, 28-448 GB RAM)
Storage-Optimized VMs
L-series: High-storage VMs for large-scale storage and file serving workloads.
Sizes: L4-L32 (4-32 vCPUs, 32-256 GB RAM)
GPU-Optimized VMs
N-series: VMs with NVIDIA Tesla GPUs for graphics rendering, AI, and deep learning workloads.
Sizes: NC6-NC24 (6-24 vCPUs, 56-224 GB RAM)
NV-series: VMs with NVIDIA Tesla GPUs for graphics rendering, AI, and deep learning workloads.
Sizes: NV6-NV24 (6-24 vCPUs, 56-224 GB RAM)
Differences between sizes
The main differences between VM sizes are:
vCPUs: The number of virtual CPUs, which affects the VM's processing power.
RAM: The amount of memory, which affects the VM's ability to handle memory-intensive workloads.
Storage: The type and amount of storage, which affects the VM's storage capacity and performance.
GPU: The presence and type of GPU, which affects the VM's ability to handle graphics rendering and AI workloads.
Networking: The VM's networking capabilities, such as the number of network interfaces and the network bandwidth.
When choosing a VM size, consider the specific requirements of your workload, including processing power, memory, storage, and networking needs.
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Azure offers a wide variety of virtual machine (VM) sizes to cater to different workload requirements.1 These sizes are categorized into families, each optimized for specific use cases.2 Here's a breakdown of some common VM families and their key differences:
General Purpose VMs
A-series: Basic, economical VMs ideal for development/testing, small databases, and low-traffic web servers.3 They offer a balance of CPU, memory, and disk resources.
B-series: Burstable VMs suitable for workloads with variable CPU usage.4 They provide a base level of performance with the ability to burst to higher performance for short periods.5
D-series: General purpose VMs with a higher CPU-to-memory ratio, suitable for many enterprise-grade applications.6
Dv3, Dv4, Dv5 series: Newer generations of D-series VMs with improved performance and features.7
Compute Optimized VMs
F-series: VMs with a high CPU-to-memory ratio, optimized for compute-intensive workloads like batch processing, video encoding, and web servers.8
Fv2-series: Newer generation of F-series VMs with improved performance.9
Memory Optimized VMs
E-series: VMs with a high memory-to-CPU ratio, ideal for memory-intensive applications like large databases, caching, and in-memory analytics.10
Ev3, Ev4, Ev5 series: Newer generations of E-series VMs with improved performance and features.11
Storage Optimized VMs
L-series: VMs optimized for high disk throughput and low latency, suitable for NoSQL databases, data warehousing, and large transactional databases.12
Lv2-series: Newer generation of L-series VMs with improved performance and features.13
High Performance Computing VMs
H-series: VMs designed for high-performance computing (HPC) workloads like simulations, financial modeling, and scientific research.14 They offer high CPU performance and network bandwidth.
HB-series: VMs optimized for HPC applications with high memory bandwidth and fast storage.15
GPU VMs
N-series: VMs with GPUs for graphics-intensive applications, machine learning, and high-performance computing.16
Key Differences Between VM Sizes
CPU cores: The number of virtual processors available to the VM.
Memory: The amount of RAM available to the VM.
Storage: The type and size of storage disks available to the VM (e.g., HDD, SSD, NVMe).17
Network bandwidth: The network throughput available to the VM.
Pricing: The cost of running the VM, which varies based on size and region.18
Azure provides tools and documentation to help you choose the right VM size for your needs. You can also resize your VMs as your needs change.19
Note: This is not an exhaustive list of all available VM sizes. Azure offers a wide range of sizes with different configurations to meet various needs.20 It's recommended to refer to the official Azure documentation for the most up-to-date information on VM sizes and their specifications.
https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/overview?form=MG0AV3&tabs=breakdownsize%2Cgen-b-fam%2Ccomputesizelist%2Cmemorysizelist%2Cstoragesizelist%2Cgpusizelist%2Cfpgasizelist%2Chpcsizelist
General Purpose VMs
A-series: Entry-level, cost-effective VMs for dev/test, small databases, and low-traffic web servers.
Sizes: A0-A8 (1-8 vCPUs, 0.75-16 GB RAM)
B-series: Economical VMs for workloads with variable CPU usage, such as web servers, small databases, and dev/test environments.
Sizes: B1S-B20 (1-20 vCPUs, 0.5-80 GB RAM)
D-series: Balanced VMs for general-purpose workloads, such as medium-traffic web servers, networks, and enterprise applications.
Sizes: D2-D96 (2-96 vCPUs, 8-384 GB RAM)
Compute-Optimized VMs
F-series: High-performance VMs for compute-intensive workloads, such as gaming, scientific modeling, and data analytics.
Sizes: F2-F72 (2-72 vCPUs, 4-144 GB RAM)
H-series: High-performance VMs for HPC workloads, such as weather forecasting, fluid dynamics, and molecular modeling.
Sizes: H8-H16r (8-16 vCPUs, 56-112 GB RAM)
Memory-Optimized VMs
E-series: High-memory VMs for memory-intensive workloads, such as large databases, data warehousing, and data analytics.
Sizes: E2-E64 (2-64 vCPUs, 16-432 GB RAM)
G-series: High-memory VMs for large-scale databases, data warehousing, and big data analytics.
Sizes: G1-G5 (2-32 vCPUs, 28-448 GB RAM)
Storage-Optimized VMs
L-series: High-storage VMs for large-scale storage and file serving workloads.
Sizes: L4-L32 (4-32 vCPUs, 32-256 GB RAM)
GPU-Optimized VMs
N-series: VMs with NVIDIA Tesla GPUs for graphics rendering, AI, and deep learning workloads.
Sizes: NC6-NC24 (6-24 vCPUs, 56-224 GB RAM)
NV-series: VMs with NVIDIA Tesla GPUs for graphics rendering, AI, and deep learning workloads.
Sizes: NV6-NV24 (6-24 vCPUs, 56-224 GB RAM)
Differences between sizes
The main differences between VM sizes are:
vCPUs: The number of virtual CPUs, which affects the VM's processing power.
RAM: The amount of memory, which affects the VM's ability to handle memory-intensive workloads.
Storage: The type and amount of storage, which affects the VM's storage capacity and performance.
GPU: The presence and type of GPU, which affects the VM's ability to handle graphics rendering and AI workloads.
Networking: The VM's networking capabilities, such as the number of network interfaces and the network bandwidth.
When choosing a VM size, consider the specific requirements of your workload, including processing power, memory, storage, and networking needs.
============================================================================================
Azure offers a wide variety of virtual machine (VM) sizes to cater to different workload requirements.1 These sizes are categorized into families, each optimized for specific use cases.2 Here's a breakdown of some common VM families and their key differences:
General Purpose VMs
A-series: Basic, economical VMs ideal for development/testing, small databases, and low-traffic web servers.3 They offer a balance of CPU, memory, and disk resources.
B-series: Burstable VMs suitable for workloads with variable CPU usage.4 They provide a base level of performance with the ability to burst to higher performance for short periods.5
D-series: General purpose VMs with a higher CPU-to-memory ratio, suitable for many enterprise-grade applications.6
Dv3, Dv4, Dv5 series: Newer generations of D-series VMs with improved performance and features.7
Compute Optimized VMs
F-series: VMs with a high CPU-to-memory ratio, optimized for compute-intensive workloads like batch processing, video encoding, and web servers.8
Fv2-series: Newer generation of F-series VMs with improved performance.9
Memory Optimized VMs
E-series: VMs with a high memory-to-CPU ratio, ideal for memory-intensive applications like large databases, caching, and in-memory analytics.10
Ev3, Ev4, Ev5 series: Newer generations of E-series VMs with improved performance and features.11
Storage Optimized VMs
L-series: VMs optimized for high disk throughput and low latency, suitable for NoSQL databases, data warehousing, and large transactional databases.12
Lv2-series: Newer generation of L-series VMs with improved performance and features.13
High Performance Computing VMs
H-series: VMs designed for high-performance computing (HPC) workloads like simulations, financial modeling, and scientific research.14 They offer high CPU performance and network bandwidth.
HB-series: VMs optimized for HPC applications with high memory bandwidth and fast storage.15
GPU VMs
N-series: VMs with GPUs for graphics-intensive applications, machine learning, and high-performance computing.16
Key Differences Between VM Sizes
CPU cores: The number of virtual processors available to the VM.
Memory: The amount of RAM available to the VM.
Storage: The type and size of storage disks available to the VM (e.g., HDD, SSD, NVMe).17
Network bandwidth: The network throughput available to the VM.
Pricing: The cost of running the VM, which varies based on size and region.18
Azure provides tools and documentation to help you choose the right VM size for your needs. You can also resize your VMs as your needs change.19
Note: This is not an exhaustive list of all available VM sizes. Azure offers a wide range of sizes with different configurations to meet various needs.20 It's recommended to refer to the official Azure documentation for the most up-to-date information on VM sizes and their specifications.
https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/overview?form=MG0AV3&tabs=breakdownsize%2Cgen-b-fam%2Ccomputesizelist%2Cmemorysizelist%2Cstoragesizelist%2Cgpusizelist%2Cfpgasizelist%2Chpcsizelist
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